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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Ilmu Komputer MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) TELKOMNIKA (Telecommunication Computing Electronics and Control) Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Jurnal Ilmiah Kursor Journal of Innovation and Applied Technology International Journal of Local Economic Governance Journal of Environmental Engineering and Sustainable Technology Jurnal Pembangunan dan Alam Lestari Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) International Journal of Advances in Intelligent Informatics Scientific Journal of Informatics Journal of Information Systems Engineering and Business Intelligence KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Knowledge Engineering and Data Science Jambura Law Review Indonesian Journal of Electrical Engineering and Computer Science International Journal of Engineering, Science and Information Technology Indexia Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) Bulletin of Culinary Art and Hospitality Bulletin of Social Informatics Theory and Application Jurnal ilmiah teknologi informasi Asia Signal and Image Processing Letters
Wayan Firdaus Mahmudy
Brawijaya University
Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation

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Journal : Indonesian Journal of Electrical Engineering and Computer Science

 1 
Optimization of Dempster-Shafer’s Believe Value Using Genetic Algorithm for Identification of Plant Diseases Jatropha Curcas Triando Hamonangan Saragih; Wayan Firdaus Mahmudy; Yusuf Priyo Anggodo
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 1: October 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i1.pp61-68

Abstract

Jatropha curcas is a plant that can be used as a substitute for diesel fuel. Lack of knowledge of farmers and the limited number of experts and extension agents into the problem of dealing with the disease Jatropha curcas plant which resulted in lower quality of Jatropha curcas. Dempster-Shafer method can be a solution for decision making based on previous research. The difference in beliefs of every expert in seeing Jatropha diseases are important because Dempster-Shafer can not solve this problem. Optimization using genetic algorithms can solve this problem. Optimization of belief values using genetic algorithms can improve the accuracy of the results of this system are using Dempster-Shafer. On the results of this system provides the highest system accuracy value, opimization of belief values using genetic algorithms gives a more significant result than the use of Dempster-Shafer only.
Jatropha Curcas Disease Identification With Extreme Learning Machine Triando Hamonangan Saragih; Diny Melsye Nurul Fajri; Wayan Firdaus Mahmudy; Abdul Latief Abadi; Yusuf Priyo Anggodo
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: November 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i2.pp883-888

Abstract

Jatropha is a plant that has many functions, but this plant can be attacked by various diseases. Expert systems can be applied in identifying so that can help both farmers and extension workers to identify the disease. one of method that can be used is Extreme Learning Machine. Extreme Learning Machine is a method of learning in Neural Network which has a one-time iteration concept in each process. In this study get a maximum accuracy of 66.67% with an average accuracy of 60.61%. This proves the identification using Extreme Learning Machine is better than the comparison method that has been done before.
K-Means Clustering and Genetic Algorithm to Solve Vehicle Routing Problem with Time Windows Problem Adyan Nur Alfiyatin; Wayan Firdaus Mahmudy; Yusuf Priyo Anggodo
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 2: August 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i2.pp462-468

Abstract

Distribution is an important aspect of industrial activity to serve customers on time with minimal operational cost. Therefore, it is necessary to design a quick and accurate distribution route. One of them can be design travel distribution route using the k-means method and genetic algorithms. This research will combine k-means method and genetic algorithm to solve VRPTW problem. K-means can do clustering properly and genetic algorithms can optimize the route. The proposed genetic algorithm employs initialize chromosome from the result of k-means and using replacement method of selection. Based on the comparison between genetic algorithm and hybrid k-means genetic algorithm proves that k-means genetic algorithm is a suitable combination method with relative low computation time, are the comparison between 2700 and 3900 seconds.
Optimization of Food Composition for Hypertensive Patient using Variable Neighborhood Search Aprilia Nur Fauziyah; Wayan Firdaus Mahmudy
Indonesian Journal of Electrical Engineering and Computer Science Vol 8, No 2: November 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v8.i2.pp327-334

Abstract

Hypertension is a major symptom that cause other diseases appear such as non-communicable diseases, cancer, and diabetes if the nutrients on hypertensive patients not controlled from the actual nutrition need. One of healthy life effort for the patients is consuming healthy food that considers level of salt in the foods. The problem to determine the food composition that considers level of salt and minimum cost of the food is solved using Variable Neighborhood Search. This study compares 3 neighborhood structures: insertion, exchange, and 2-opt. The use of 2-opt neighborhood structure gives the highest fitness averages of other neighborhood structure. Selection and arrangement of neighborhood structure in every k neighborhood have effect on the solution is obtained. The result of this study contains composition of foods with nutrients which are close to the needs of hypertension patients with attentions the sodium and minimal cost within a day.
Anomaly-based intrusion detector system using restricted growing self organizing map Tomi Yahya Christyawan; Ahmad Afif Supianto; Wayan Firdaus Mahmudy
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 3: March 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i3.pp919-926

Abstract

The rapid development of internet and network technology followed by malicious threats and attacks on networks and computers. Intrusion detection system (IDS) was developed to solve that problems. The development of IDS using machine learning is needed for classifying the attacks. One method of the classification is Self-Organizing Map (SOM). SOM able to perform classification and visualization in learning process to gain new knowledge. However, the SOM has less efficient in learning process when applied in Big Data. This study proposes Restricted Growing SOM method with clustering reference vector (RGSOM-CRV) and Parallel RGSOM-CRV to improve SOM efficiency in classification with accuracy consideration to solve Big Data problem. Growing process in RGSOM is restricted by maximum nodes and growing threshold, the reupdate weight process will update unused reference vector when map size already maximum, these two processes solve the consuming time of regular GSOM. From the results of this research against KDD Cup 1999 dataset, proposed method Parallel RGSOM-CRV able to give 91.86% accuracy, 20.58% false alarm rate, 95.32% recall or detection rate, and precision is 94.35% and time consuming is outperform than regular Growing SOM. This proposed method is very promising to handle big data problems compared with other methods.
Android Malware Detection Using Backpropagation Neural Network Fais Al Huda; Wayan Firdaus Mahmudy; Herman Tolle
Indonesian Journal of Electrical Engineering and Computer Science Vol 4, No 1: October 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v4.i1.pp240-244

Abstract

The rapid growing adoption of android operating system around the world affects the growth of malware that attacks this platform. One possible solution to overcome the threat of malware is building a comprehensive system to detect existing malware. This paper proposes multilayer perceptron artificial neural network trained with backpropagation algorithm to determine an application is malware or non-malware application which is often called benign application. The parameters that used in this study based on the list of permissions in the manifest file, the battery rating based on permission, and the size of the application file. Final weights obtained in the training phase will be used in mobile applications for malware detection. The experimental results show that the proposed method for detection of malware on android is effective. The effectiveness is demonstrated by the results of the accuracy of the system developed in this study is relatively high to recognize existing malware samples.
Optimization of Ship’s Route Scheduling Using Genetic Algorithm Vivi Nur Wijayaningrum; Wayan Firdaus Mahmudy
Indonesian Journal of Electrical Engineering and Computer Science Vol 2, No 1: April 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v2.i1.pp180-186

Abstract

Route scheduling is a quite complicated process because it involves some determinant factors. Several methods have been used to help resolve the NP-hard problems. This research uses genetic algorithm to assist in optimizing ship scheduling, that where there are several ports to be visited by some ships. The goal is to divide the ship to go to a specific port so that each port is only visited by one ship to minimize the total distance of all ships. The computational experiment produces optimal parameters such as the number of popsize is 30, the number of generations is 100, crossover rate value is 0.3 and mutation rate values is 0.7. The final results is an optimal ship route by minimizing the distance of each ship.
Kenaf plant pest and disease detection using faster regional based convolutional neural network Alfita Rakhmandasari; Wayan Firdaus Mahmudy; Titiek Yulianti
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 1: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i1.pp198-207

Abstract

Kenaf plant is a fibre plant whose stem bark is taken to be used as raw material for making geo-textile, particleboard, pulp, fiber drain, fiber board, and paper. The presence of plant pests and diseases that attack causes crop production to decrease. The detection of pests and diseases by farmers may be a challenging task. The detection can be done using artificial intelligence-based method. Convolutional neural networks (CNNs) are one of the most popular neural network architectures and have been successfully implemented for image classification. However, the CNN method is still considered a long time in the process, so this method was developed into namely faster regional based convolution neural network (RCNN). As the selection of the input features largely determines the accuracy of the results, a pre-processing procedure is developed to transform the kenaf plant image into input features of faster RCNN. A computational experiment proves that the faster RCNN has a very short computation time by completing 10000 iterations in 3 hours compared to convolutional neural network (CNN) completing 100 iterations at the same time. Furthermore, Faster RCNN gets 77.50% detection accuracy and bounding box accuracy 96.74% while CNN gets 72.96% detection accuracy at 400 epochs. The results also prove that the selection of input features and its pre-processing procedure could produce a high accuracy of detection. 
Offline Signature Recognition using Back Propagation Neural Network Asyrofa Rahmi; Vivi Nur Wijayaningrum; Wayan Firdaus Mahmudy; Andi Maulidinnawati A. K. Parewe
Indonesian Journal of Electrical Engineering and Computer Science Vol 4, No 3: December 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v4.i3.pp678-683

Abstract

The signature recognition is a difficult process as it requires several phases. A failure in a phase will significantly reduce the recognition accuracy. Artificial Neural Network (ANN) believed to be used to assist in the recognition or classification of the signature. In this study, the ANN algorithm used is Back Propagation. A mechanism to adaptively adjust the learning rate is developed to improve the system accuracy. The purpose of this study is to conduct the recognition of a number of signatures so that can be known whether the recognition which is done by using the Back Propagation is appropriate or not. The testing results performed by using learning rate of 0.64, the number of iterations is 100, and produces an accuracy value of 63%.
Co-Authors A.N. Afandi Abdul Latief Abadi Abdul Latief Abadi Achmad Arwan Achmad Basuki Achmad Ridok Adimoelja, Ariawan Aditama, Gustian Adyan Nur Alfiyatin Agi Putra Kharisma, Agi Putra Agung Mustika Rizki Agung Mustika Rizki, Agung Mustika Agung Setia Budi Agus Naba Agus Wahyu Widodo Agus Wahyu Widodo Agus Wahyu Widodo, Agus Wahyu Ahmad Afif Supianto Ahmad Afif Supianto Ahmad Afif Supianto Aji Prasetya Wibawa Al Khuluqi, Mabafasa Alauddin, Mukhammad Wildan Alfiani Fitri Alfita Rakhmandasari Alfiyatin, Adyan Nur Alqorni, Faiz Amalia Kartika Ariyani Amalia Kartika Ariyani Amalia Kartika Ariyani Anantha Yullian Sukmadewa Andi Kurniawan Andi Maulidinnawati A K Parewe Andi Maulidinnawati A. K. Parewe Andreas Nugroho Sihananto Andreas Pardede Andreas Patuan G. Pardede Andrew Nafalski Angga Vidianto Aprilia Nur Fauziyah Aprilia Nur Fauziyah Arief Andy Soebroto Arinda Hapsari Achnas Armanda, Rifki Setya Arviananda Bahtiar Arya, Putu Bagus Asyrofa Rahmi Asyrofa Rahmi Asyrofa Rahmi Asyrofa Rahmi Asyrofa Rahmi, Asyrofa Bagus Priambodo Bayu Rahayudi Binti Robiyatul Musanah Budi Darma Setiawan Burhan, M.Shochibul Cahya, Reiza Adi Cahyo Prayogo, Cahyo Candra Dewi Candra Fajri Ananda Cleoputri Yusainy Darmawan, Abizard Hashfi Dea Widya Hutami Dhaifullah, Afif Naufal Diah Anggraeni Pitaloka Didik Suprayogo Dinda Novitasari Dinda Novitasari, Dinda Diny Melsye Nurul Fajri Dita Sundarningsih Durrotul Fakhiroh Dyan Putri Mahardika Edi Satriyanto Edy Santoso Eko Widaryanto Elta Sonalitha Ervin Yohannes Evi Nur Azizah Fadhli Almu’iini Ahda Fais Al Huda Fajri, Diny Melsye Nurul Fatchurrochman Fatchurrochman Fatwa Ramdani, Fatwa Fauzi, Muhammad Rifqi Fauziatul Munawaroh Febriyana, Ria Fendy Yulianto Fitra Abdurrachman Bachtiar Fitri Anggarsari Fitria Dwi Nurhayati Gayatri Dwi Santika Ghozali Maski Grady Davinsyah Gusti Ahmad Fanshuri Alfarisy Gusti Ahmad Fanshuri Alfarisy, Gusti Ahmad Fanshuri Gusti Eka Yuliastuti Hafidz Ubaidillah Hamdianah, Andi Hanggara , Buce Trias Herman Tolle Hernando, Deo Heru Nurwarsito Hidayat, Luthfi Hilman Nuril Hadi Ida Wahyuni Imada Nur Afifah Imam Cholisoddin Imam Cholissodin Imam Cholissodin Imam Cholissodin Indriati Indriati Irvi Oktanisa Ishardita Pambudi Tama Ismiarta Aknuranda Jauhari, Farid Khozaimi, Ach. Kukuh Tejomurti, Kukuh Kuncahyo Setyo Nugroho Kuncahyo Setyo Nugroho Kurnianingtyas, Diva Lily Montarcih Limantara M Chandra Cahyo Utomo M Fadli Ridhani M Shochibul Burhan, M Shochibul M. Shochibul Burhan M. Zainal Arifin Mabafasa Al Khuluqi Mar'i, Farhanna Marji Marji Mayang Anglingsari Putri, Mayang Anglingsari Mochamad Anshori Moh. Khusaini Moh. Sholichin Moh. Zoqi Sarwani Mohammad Zoqi Sarwani Mohammad Zoqi Sarwani, Mohammad Zoqi Mu’asyaroh, Fita Lathifatul Muh. Arif Rahman Muhammad Ardhian Megatama Muhammad Faris Mas'ud Muhammad Halim Natsir Muhammad Isradi Azhar Muhammad Khaerul Ardi Muhammad Noor Taufiq Muhammad Rivai Muhammad Rofiq Nadia Roosmalita Sari Nadia Roosmalita Sari Nadia Roosmalita Sari Nadya Oktavia Rahardiani Nashi Widodo Ni Wayan Surya Wardhani Nindynar Rikatsih Novanto Yudistira Novi Nur Putriwijaya Nurizal Dwi Priandani Nurul Hidayat Oakley, Simon Oktanisa, Irvi Philip Faster Eka Adipraja Prayudi Lestantyo Purnomo Budi Santoso Putra, Firnanda Al Islama Achyunda Putri Hasan, Vitara Nindya Putu Indah Ciptayani Qoirul Kotimah Rachmansyah, Ghenniy Rachmawati, Christina Rani Kurnia Rayandra Yala Pratama, Rayandra Yala Retno Dewi Anissa Riani, Garsinia Ely Rifa’i, Muhaimin Rikatsih, Nindynar Rinda Wahyuni Rizal Setya Perdana Rizal Setya Perdana Rizdania, Rizdania Rizka Suhana Rizki Ramadhan Rody, Rafiuddin Ruth Ema Febrita Ryan Iriany S, M Zaki Samaher . Saragih, Triando Hamonangan Sari, Nadia Roosmalita Sari, Nadia Roosmalita Selly Kurnia Sari Setyawan Purnomo Sakti Sudarto Sudarto Sukarmi Sukarmi, Sukarmi Sulistyo, Danang Arbian Sutrisno . Sutrisno Sutrisno Syafrial Syafrial Syafrial Syafrial Syaiful Anam Syandri, Hafrijal Tirana Noor Fatyanosa, Tirana Noor Titiek Yulianti Titiek Yulianti Titiek YULIANTI Tomi Yahya Christyawan Tri Halomoan Simanjuntak Ullump Pratiwi Utaminingrum, Fitri Utomo, M. Chandra Cahyo Vivi Nur Wijayaningrum Wahyuni, Ida Widdia Lesmawati Windi Artha Setyowati Yeni Herawati Yogi Pinanda Yogie Susdyastama Putra Yudha Alif Aulia Yudha Alif Auliya Yudha Alif Auliya, Yudha Alif Yulia Trianandi Yusuf Priyo Anggodo Yusuf Priyo Anggodo Yusuf Priyo Anggodo Yusuf Priyo Anggodo, Yusuf Priyo